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Merge origin/main, resolve CHANGELOG conflict, bump to v0.13.7.0

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Main landed v0.13.6.0 (GStack Learns) while this branch had v0.13.6.0
(Community Wave). Resolved by keeping both entries and bumping this
branch to v0.13.7.0. Regenerated SKILL.md files to pick up new learn
skill and apply the find -exec rm fix from this branch.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
This commit is contained in:
Garry Tan
2026-03-29 20:03:18 -07:00
parent fed92d053c ae0a9ad195
commit f21edb5943
49 changed files with 2379 additions and 3 deletions
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retro/SKILL.md
+33
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@@ -61,6 +61,15 @@ for _PF in $(find ~/.gstack/analytics -maxdepth 1 -name '.pending-*' 2>/dev/null
fi
break
done
# Learnings count
eval "$(~/.claude/skills/gstack/bin/gstack-slug 2>/dev/null)" 2>/dev/null || true
_LEARN_FILE="${GSTACK_HOME:-$HOME/.gstack}/projects/${SLUG:-unknown}/learnings.jsonl"
if [ -f "$_LEARN_FILE" ]; then
_LEARN_COUNT=$(wc -l < "$_LEARN_FILE" 2>/dev/null | tr -d ' ')
echo "LEARNINGS: $_LEARN_COUNT entries loaded"
else
echo "LEARNINGS: 0"
fi
```
If `PROACTIVE` is `"false"`, do not proactively suggest gstack skills AND do not
@@ -625,6 +634,30 @@ For each contributor (including the current user), compute:
**If there are Co-Authored-By trailers:** Parse `Co-Authored-By:` lines in commit messages. Credit those authors for the commit alongside the primary author. Note AI co-authors (e.g., `noreply@anthropic.com`) but do not include them as team members — instead, track "AI-assisted commits" as a separate metric.
## Capture Learnings
If you discovered a non-obvious pattern, pitfall, or architectural insight during
this session, log it for future sessions:
```bash
~/.claude/skills/gstack/bin/gstack-learnings-log '{"skill":"retro","type":"TYPE","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":N,"source":"SOURCE","files":["path/to/relevant/file"]}'
```
**Types:** `pattern` (reusable approach), `pitfall` (what NOT to do), `preference`
(user stated), `architecture` (structural decision), `tool` (library/framework insight).
**Sources:** `observed` (you found this in the code), `user-stated` (user told you),
`inferred` (AI deduction), `cross-model` (both Claude and Codex agree).
**Confidence:** 1-10. Be honest. An observed pattern you verified in the code is 8-9.
An inference you're not sure about is 4-5. A user preference they explicitly stated is 10.
**files:** Include the specific file paths this learning references. This enables
staleness detection: if those files are later deleted, the learning can be flagged.
**Only log genuine discoveries.** Don't log obvious things. Don't log things the user
already knows. A good test: would this insight save time in a future session? If yes, log it.
### Step 10: Week-over-Week Trends (if window >= 14d)
If the time window is 14 days or more, split into weekly buckets and show trends:
retro/SKILL.md.tmpl
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@@ -277,6 +277,8 @@ For each contributor (including the current user), compute:
**If there are Co-Authored-By trailers:** Parse `Co-Authored-By:` lines in commit messages. Credit those authors for the commit alongside the primary author. Note AI co-authors (e.g., `noreply@anthropic.com`) but do not include them as team members — instead, track "AI-assisted commits" as a separate metric.
{{LEARNINGS_LOG}}
### Step 10: Week-over-Week Trends (if window >= 14d)
If the time window is 14 days or more, split into weekly buckets and show trends: